This paper presents a novel dynamic quantitative risk assessment method to analyze the operational performance of chemical processes. Unlike traditional methods, the proposed method estimates the probability of undesirable event occurrence by monitoring multiple key variables in the process. This probability is continuously updated considering real-time disturbances in the variables. The consequences are estimated using dynamic loss functions developed considering multiple key state variables. As a result, the process' operational performance is assessed dynamically in the form of quantitative risk (dollar) value. The quantitative dynamic risk value helps to make swift operational decisions to maintain the process within the safer operating limits, thus preventing untoward incidents/accidents. To demonstrate the efficacy of the proposed methodology, it is tested on two case studies, a simple tank system and the benchmark Tennessee Eastman process. (C) 2015 Elsevier Ltd. All rights reserved.